Diabetic nephropathy (DN), causing 46% of all chronic kidney disease (CKD), develops slowly and there may be severe structural damage before DN is clinically apparent. 85% of DN occurs in type 2 (T2DM) diabetes. DN risk is extraordinarily high among T2DM American Indians. In Caucasian T2DM, more complex patterns of renal injury affect clinical outcomes and confuse clinical categorizations. Together, this consortium [Universities of Minnesota (U of MN) and Padova, Italy, and the Phoenix Epidemiology and Clinical Research Branch of NIDDK] have performed most of the research kidney biopsies in T1DM and T2DM in the world. The large Pima Indian T2DM cohort, followed longitudinally for decades, has stored samples through the entire natural history of DN. A major advantage is our ability to study biomarkers of early DN structural changes prior to detectability of functional abnormalities. Also, since microalbuminuria (MA) is associated with only a 35-45% risk of progression to proteinuria (P), we will search for predictors of this progression. Finally, in the non-biopsy Pima cohort, we can examine predictors of progression rates from MA to P to ESRD. Our aims are to: (1) develop a DN risk index (DNRI) from albumin excretion rate and other variables (e.g., duration, glycemia, blood pressure, lipid levels, etc.) for Tl DM and T2DM patients (pts), (2) determine whether urine proteomic and/or metabolomic patterns predict the underlying renal structure or changes in structure or clinical progression, (3) determine the changes in urinary proteomic and/or metabolomic patterns as DN progresses from early DN to advanced CKD. Cohorts include>500 NA T1DM pts, with baseline and 5-yr biopsies and baseline and interval clinical and renal functional measures. T2DM biopsy populations include >200 Pima and >130 Northern Italian pts. In addition there are >2000 Pima pts without renal biopsies. We will initially use non-targeted proteomic and metabolomic methods on urine samples of selected pt subsets to derive more targeted assays for broader surveys of these cohorts. Studies will be done in world class mass spectroscopy facilities at the U of MN. Data analysis involves repeated measures (Wake Forest U) and Bioinformatics (Dartmouth) statistical expertise. Although focused on biomarker discovery, capabilities for negotiating validation regulatory processes are available at the U/MN.